GREENPEG's toolset for Province scale pegmatite exploration: interactive workflows
Creators
- 1. Department of Geosciences, Environment and Spatial Planning, Faculty of Sciences, University of Porto
- 2. ICT (Institute of Earth Sciences) – Porto Pole (Portugal)
Description
The EU-funded GREENPEG project aims to develop multi-method exploration toolsets for the identification of buried, small-scale (<5 million m3) rare metal pegmatite deposits. GREENPEG divides the exploration workflow into three major scales: province scale (500 to 10,000 km2), district scale (25-500 km2) and prospect scale (<25 km2). This record presents the interactive toolsets (in the form of workflows) for province-scale pegmatite exploration: Spectral identification of outcropping pegmatites; Morphological identification of pegmatites using laser imaging, detection and ranging (LiDAR); and Remote-sensing-supported analysis of regional structures. A spectral library of pegmatite ores and their wall rocks is already published and available.
Notes
The workflows were developed as part of the GREENPEG project: New Exploration Tools for European Pegmatite Green-Tech Resources. The project is funded by the European Commission's Horizon 2020 innovation programme under grant agreement No 869274. For more information on the project, please visit the project website: https://www.greenpeg.eu/
Files
Toolset_Spectral identification of outcropping pegmatites.pdf
Additional details
Related works
- Is supplemented by
- Dataset: 10.5281/zenodo.6518318 (DOI)
Funding
References
- Cardoso-Fernandes, J., Teodoro, A.C., and Lima, A., 2019, Remote sensing data in lithium (Li) exploration: A new approach for the detection of Li-bearing pegmatites: International Journal of Applied Earth Observation and Geoinformation, vol. 76, p. 10-25. (https://doi.org/10.1016/j.jag.2018.11.001).
- Cardoso-Fernandes, J., Teodoro, A.C., Lima, A., Perrotta, M., and Roda-Robles, E., 2020, detecting lithium (Li) mineralizations from Space: Current research and future perspectives: Applied Sciences, vol. 10(5), 1785. (https://doi.org/10.3390/app10051785).
- Joana Cardoso-Fernandes, Ana Claudia Teodoro, Alexandre Lima, Julian Menuge, Marco Brönner, Ralf Steiner, "Sentinel-1 and ALOS data for lineament extraction: a comparative study," Proc. SPIE 12268, Earth Resources and Environmental Remote Sensing/GIS Applications XIII, 122680X (26 October 2022); doi: 10.1117/12.2636117
- D. Santos, J. Cardoso-Fernandes, A. Lima, A. C. Teodoro, "The potential of spectral unmixing method applied to PRISMA hyperspectral images in the identification of Li minerals: an evaluation for prospecting purposes," Proc. SPIE 12268, Earth Resources and Environmental Remote Sensing/GIS Applications XIII, 1226811 (26 October 2022); doi: 10.1117/12.2636034
- Santos, D.; Cardoso-Fernandes, J.; Lima, A.; Müller, A.; Brönner, M.; Teodoro, A.C. Spectral Analysis to Improve Inputs to Random Forest and Other Boosted Ensemble Tree-Based Algorithms for Detecting NYF Pegmatites in Tysfjord, Norway. Remote Sens. 2022, 14, 3532. https://doi.org/10.3390/rs14153532